Overview

Dataset statistics

Number of variables14
Number of observations26064
Missing cells16083
Missing cells (%)4.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory112.0 B

Variable types

DateTime1
Numeric13

Alerts

Power (kW) is highly overall correlated with Rear bearing temperature (°C) and 6 other fieldsHigh correlation
Wind direction (°) is highly overall correlated with Nacelle position (°)High correlation
Nacelle position (°) is highly overall correlated with Wind direction (°)High correlation
blade_angle is highly overall correlated with Rear bearing temperature (°C)High correlation
Rear bearing temperature (°C) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Rotor speed (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Generator RPM (RPM) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Nacelle ambient temperature (°C) is highly overall correlated with Metal particle count counterHigh correlation
Front bearing temperature (°C) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Tower Acceleration X (mm/ss) is highly overall correlated with Power (kW) and 5 other fieldsHigh correlation
Wind speed (m/s) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Tower Acceleration y (mm/ss) is highly overall correlated with Power (kW) and 6 other fieldsHigh correlation
Metal particle count counter is highly overall correlated with Nacelle ambient temperature (°C)High correlation
blade_angle has 2247 (8.6%) missing valuesMissing
Rear bearing temperature (°C) has 2247 (8.6%) missing valuesMissing
Nacelle ambient temperature (°C) has 2247 (8.6%) missing valuesMissing
Front bearing temperature (°C) has 2247 (8.6%) missing valuesMissing
Tower Acceleration X (mm/ss) has 2247 (8.6%) missing valuesMissing
Tower Acceleration y (mm/ss) has 2247 (8.6%) missing valuesMissing
Metal particle count counter has 2247 (8.6%) missing valuesMissing
# Date and time has unique valuesUnique
blade_angle has 9615 (36.9%) zerosZeros
Rotor speed (RPM) has 1087 (4.2%) zerosZeros

Reproduction

Analysis started2023-07-08 12:02:40.872188
Analysis finished2023-07-08 12:02:57.810454
Duration16.94 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

# Date and time
Date

Distinct26064
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size203.8 KiB
Minimum2021-01-01 00:00:00
Maximum2021-06-30 23:50:00
2023-07-08T17:32:57.865375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:57.969036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Power (kW)
Real number (ℝ)

Distinct25885
Distinct (%)99.5%
Missing59
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean595.4956
Minimum-16.138471
Maximum2077.5231
Zeros1
Zeros (%)< 0.1%
Negative3609
Negative (%)13.8%
Memory size203.8 KiB
2023-07-08T17:32:58.079556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-16.138471
5-th percentile-1.5442894
Q177.913928
median306.51721
Q3934.70809
95-th percentile2022.137
Maximum2077.5231
Range2093.6615
Interquartile range (IQR)856.79417

Descriptive statistics

Standard deviation665.89302
Coefficient of variation (CV)1.1182165
Kurtosis-0.20667147
Mean595.4956
Median Absolute Deviation (MAD)293.10571
Skewness1.0832722
Sum15485863
Variance443413.51
MonotonicityNot monotonic
2023-07-08T17:32:58.174328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.0700000003 6
 
< 0.1%
-0.7099999785 6
 
< 0.1%
-0.8100000024 6
 
< 0.1%
-0.8299999833 5
 
< 0.1%
-0.8700000048 5
 
< 0.1%
-0.8199999928 5
 
< 0.1%
-0.7799999714 4
 
< 0.1%
-1.289999962 4
 
< 0.1%
-1.24000001 4
 
< 0.1%
-0.7300000191 3
 
< 0.1%
Other values (25875) 25957
99.6%
(Missing) 59
 
0.2%
ValueCountFrequency (%)
-16.13847065 1
< 0.1%
-15.74262075 1
< 0.1%
-15.02378969 1
< 0.1%
-14.72013049 1
< 0.1%
-13.70911815 1
< 0.1%
-13.31936014 1
< 0.1%
-12.35454672 1
< 0.1%
-12.35243655 1
< 0.1%
-12.32999992 1
< 0.1%
-12.05134406 1
< 0.1%
ValueCountFrequency (%)
2077.523059 1
< 0.1%
2076.688605 1
< 0.1%
2074.871912 1
< 0.1%
2074.051886 1
< 0.1%
2073.118726 1
< 0.1%
2071.091321 1
< 0.1%
2071.053126 1
< 0.1%
2070.834131 1
< 0.1%
2070.487347 1
< 0.1%
2070.176807 1
< 0.1%

Wind direction (°)
Real number (ℝ)

Distinct25810
Distinct (%)99.3%
Missing59
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean177.32476
Minimum0
Maximum359.98635
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:32:58.273529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.846005
Q170.03353
median197.90745
Q3261.9831
95-th percentile329.22238
Maximum359.98635
Range359.98635
Interquartile range (IQR)191.94957

Descriptive statistics

Standard deviation104.11492
Coefficient of variation (CV)0.58714259
Kurtosis-1.2986515
Mean177.32476
Median Absolute Deviation (MAD)89.303323
Skewness-0.14373966
Sum4611330.5
Variance10839.917
MonotonicityNot monotonic
2023-07-08T17:32:58.373759image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38.00999832 4
 
< 0.1%
29.69000053 4
 
< 0.1%
15.98999977 4
 
< 0.1%
16.60000038 3
 
< 0.1%
39.95000076 3
 
< 0.1%
36.15999985 3
 
< 0.1%
14.61999989 3
 
< 0.1%
30.90999985 3
 
< 0.1%
35.97999954 3
 
< 0.1%
41.97000122 3
 
< 0.1%
Other values (25800) 25972
99.6%
(Missing) 59
 
0.2%
ValueCountFrequency (%)
0 1
< 0.1%
0.008690643942 1
< 0.1%
0.01750601148 1
< 0.1%
0.03866694169 1
< 0.1%
0.05000000075 1
< 0.1%
0.08592362473 1
< 0.1%
0.1132764624 1
< 0.1%
0.1172988072 1
< 0.1%
0.1267089202 1
< 0.1%
0.1589554723 1
< 0.1%
ValueCountFrequency (%)
359.9863509 1
< 0.1%
359.9686965 1
< 0.1%
359.9560594 1
< 0.1%
359.8896899 1
< 0.1%
359.8697424 1
< 0.1%
359.811447 1
< 0.1%
359.7924104 1
< 0.1%
359.7899285 1
< 0.1%
359.7845963 1
< 0.1%
359.7799988 1
< 0.1%

Nacelle position (°)
Real number (ℝ)

Distinct6071
Distinct (%)23.3%
Missing59
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean178.79759
Minimum0.12416326
Maximum359.96381
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:32:58.481309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.12416326
5-th percentile20.415356
Q172.001205
median199.49537
Q3263.75746
95-th percentile331.02502
Maximum359.96381
Range359.83964
Interquartile range (IQR)191.75626

Descriptive statistics

Standard deviation104.37647
Coefficient of variation (CV)0.5837689
Kurtosis-1.2929331
Mean178.79759
Median Absolute Deviation (MAD)88.725148
Skewness-0.15544878
Sum4649631.3
Variance10894.448
MonotonicityNot monotonic
2023-07-08T17:32:58.581670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197.1226501 130
 
0.5%
74.19631958 121
 
0.5%
238.8301086 119
 
0.5%
43.4646492 118
 
0.5%
318.9523315 116
 
0.4%
193.8299561 114
 
0.4%
244.3179321 111
 
0.4%
20.41535568 111
 
0.4%
204.805603 106
 
0.4%
188.3421326 105
 
0.4%
Other values (6061) 24854
95.4%
ValueCountFrequency (%)
0.1241632572 1
 
< 0.1%
0.200000003 1
 
< 0.1%
0.3224445616 1
 
< 0.1%
0.6600000262 15
0.1%
0.6603088379 1
 
< 0.1%
0.6727723324 1
 
< 0.1%
0.7203662711 1
 
< 0.1%
0.7356911965 1
 
< 0.1%
0.8956863814 1
 
< 0.1%
0.9056903077 1
 
< 0.1%
ValueCountFrequency (%)
359.9638053 1
 
< 0.1%
359.8913944 1
 
< 0.1%
359.7820728 1
 
< 0.1%
359.7590393 1
 
< 0.1%
359.5644923 1
 
< 0.1%
359.5622253 5
< 0.1%
359.5599976 3
< 0.1%
359.2277452 1
 
< 0.1%
359.1460502 1
 
< 0.1%
359.1134923 1
 
< 0.1%

blade_angle
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct9712
Distinct (%)40.8%
Missing2247
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean8.5047843
Minimum0
Maximum92.529999
Zeros9615
Zeros (%)36.9%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:32:58.689146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.1475
Q33.5578334
95-th percentile44.993334
Maximum92.529999
Range92.529999
Interquartile range (IQR)3.5578334

Descriptive statistics

Standard deviation19.844217
Coefficient of variation (CV)2.3333005
Kurtosis7.5475932
Mean8.5047843
Median Absolute Deviation (MAD)0.1475
Skewness2.8081588
Sum202558.45
Variance393.79296
MonotonicityNot monotonic
2023-07-08T17:32:58.789233image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9615
36.9%
44.99333445 1141
 
4.4%
44.99000168 668
 
2.6%
89.98999786 570
 
2.2%
0.02450000048 236
 
0.9%
1.49000001 132
 
0.5%
0.02466666698 118
 
0.5%
1.49333334 116
 
0.4%
0.04900000095 72
 
0.3%
0.07350000143 47
 
0.2%
Other values (9702) 11102
42.6%
(Missing) 2247
 
8.6%
ValueCountFrequency (%)
0 9615
36.9%
0.0001666666629 11
 
< 0.1%
0.0001754385926 1
 
< 0.1%
0.0003333333259 7
 
< 0.1%
0.0004999999888 12
 
< 0.1%
0.0004999999888 3
 
< 0.1%
0.0006666666518 1
 
< 0.1%
0.000784313708 1
 
< 0.1%
0.0008333333147 3
 
< 0.1%
0.0008333333147 2
 
< 0.1%
ValueCountFrequency (%)
92.52999878 2
 
< 0.1%
92.48999786 36
0.1%
92.43000285 2
 
< 0.1%
92.32666524 1
 
< 0.1%
92.04200007 1
 
< 0.1%
91.87333425 5
 
< 0.1%
91.87000275 3
 
< 0.1%
91.85666656 32
0.1%
91.85333506 1
 
< 0.1%
91.85183474 2
 
< 0.1%

Rear bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20165
Distinct (%)84.7%
Missing2247
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean62.03309
Minimum9.385
Maximum74.872501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:32:58.888673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum9.385
5-th percentile34.7385
Q159.9425
median66.697501
Q369.360002
95-th percentile71.943
Maximum74.872501
Range65.487501
Interquartile range (IQR)9.4175016

Descriptive statistics

Standard deviation12.173927
Coefficient of variation (CV)0.19624893
Kurtosis4.5402559
Mean62.03309
Median Absolute Deviation (MAD)3.515922
Skewness-2.1216782
Sum1477442.1
Variance148.20451
MonotonicityNot monotonic
2023-07-08T17:32:59.134551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69.01499977 8
 
< 0.1%
68.78000183 7
 
< 0.1%
66.87250061 6
 
< 0.1%
69.00999985 5
 
< 0.1%
68.66999931 5
 
< 0.1%
69.475 5
 
< 0.1%
67.21000023 5
 
< 0.1%
68.06499977 5
 
< 0.1%
69.84250069 5
 
< 0.1%
68.80750084 5
 
< 0.1%
Other values (20155) 23761
91.2%
(Missing) 2247
 
8.6%
ValueCountFrequency (%)
9.385000038 1
< 0.1%
9.530000067 1
< 0.1%
9.550000191 1
< 0.1%
9.562500238 1
< 0.1%
9.5900002 1
< 0.1%
9.635000181 1
< 0.1%
9.657500029 1
< 0.1%
9.682500029 1
< 0.1%
9.690000057 1
< 0.1%
9.695237886 1
< 0.1%
ValueCountFrequency (%)
74.87250061 1
< 0.1%
74.80999985 1
< 0.1%
74.54999904 1
< 0.1%
74.48750038 1
< 0.1%
74.40882335 1
< 0.1%
74.225 1
< 0.1%
74.19999695 1
< 0.1%
74.19499969 1
< 0.1%
74.00250015 1
< 0.1%
73.98249893 1
< 0.1%

Rotor speed (RPM)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23449
Distinct (%)90.2%
Missing59
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean9.8615091
Minimum0
Maximum15.341406
Zeros1087
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:32:59.240993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.063601813
Q18.14827
median9.9825242
Q313.848652
95-th percentile15.163874
Maximum15.341406
Range15.341406
Interquartile range (IQR)5.7003817

Descriptive statistics

Standard deviation4.4551203
Coefficient of variation (CV)0.45176862
Kurtosis-0.0005694654
Mean9.8615091
Median Absolute Deviation (MAD)2.1154997
Skewness-0.81064723
Sum256448.54
Variance19.848097
MonotonicityNot monotonic
2023-07-08T17:32:59.340074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1087
 
4.2%
8.140000343 244
 
0.9%
8.149999619 54
 
0.2%
8.159999847 31
 
0.1%
8.170000076 29
 
0.1%
8.18999958 15
 
0.1%
8.210000038 15
 
0.1%
8.180000305 14
 
0.1%
8.220000267 13
 
< 0.1%
8.229999542 12
 
< 0.1%
Other values (23439) 24491
94.0%
(Missing) 59
 
0.2%
ValueCountFrequency (%)
0 1087
4.2%
0.0006120000762 1
 
< 0.1%
0.001046500169 1
 
< 0.1%
0.002200000396 1
 
< 0.1%
0.003828000161 1
 
< 0.1%
0.00645187567 1
 
< 0.1%
0.006628501229 1
 
< 0.1%
0.007437501568 1
 
< 0.1%
0.009295001859 1
 
< 0.1%
0.009688002057 1
 
< 0.1%
ValueCountFrequency (%)
15.34140596 1
< 0.1%
15.31170827 1
< 0.1%
15.2950948 1
< 0.1%
15.29436681 1
< 0.1%
15.29392254 1
< 0.1%
15.28798596 1
< 0.1%
15.28147741 1
< 0.1%
15.27871205 1
< 0.1%
15.27434398 1
< 0.1%
15.26861027 1
< 0.1%

Generator RPM (RPM)
Real number (ℝ)

Distinct25773
Distinct (%)99.1%
Missing59
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean1167.8897
Minimum-1.9950131
Maximum1809.342
Zeros13
Zeros (%)< 0.1%
Negative803
Negative (%)3.1%
Memory size203.8 KiB
2023-07-08T17:32:59.449286image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-1.9950131
5-th percentile10.402327
Q1966.56435
median1183.141
Q31638.6062
95-th percentile1793.7765
Maximum1809.342
Range1811.3371
Interquartile range (IQR)672.04188

Descriptive statistics

Standard deviation527.01769
Coefficient of variation (CV)0.45125641
Kurtosis0.0077710452
Mean1167.8897
Median Absolute Deviation (MAD)250.10932
Skewness-0.81670365
Sum30370970
Variance277747.64
MonotonicityNot monotonic
2023-07-08T17:32:59.547385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
969.9799805 14
 
0.1%
0 13
 
< 0.1%
970.0599976 10
 
< 0.1%
970.0100098 10
 
< 0.1%
970.039978 9
 
< 0.1%
969.9199829 8
 
< 0.1%
970 8
 
< 0.1%
970.0300293 8
 
< 0.1%
969.960022 7
 
< 0.1%
969.9699707 7
 
< 0.1%
Other values (25763) 25911
99.4%
(Missing) 59
 
0.2%
ValueCountFrequency (%)
-1.995013079 1
< 0.1%
-1.924755771 1
< 0.1%
-1.809707439 1
< 0.1%
-1.761012068 1
< 0.1%
-1.701108009 1
< 0.1%
-1.66379685 1
< 0.1%
-1.642783273 1
< 0.1%
-1.600799957 1
< 0.1%
-1.587375831 1
< 0.1%
-1.579194132 1
< 0.1%
ValueCountFrequency (%)
1809.342041 1
< 0.1%
1807.368015 1
< 0.1%
1807.082594 1
< 0.1%
1806.993273 1
< 0.1%
1806.981155 1
< 0.1%
1806.89621 1
< 0.1%
1806.859468 1
< 0.1%
1806.770227 1
< 0.1%
1806.663443 1
< 0.1%
1806.488445 1
< 0.1%

Nacelle ambient temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18506
Distinct (%)77.7%
Missing2247
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean8.4537269
Minimum-3.54
Maximum27.915
Zeros0
Zeros (%)0.0%
Negative1071
Negative (%)4.1%
Memory size203.8 KiB
2023-07-08T17:32:59.650603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-3.54
5-th percentile0.2045
Q14.5025
median7.9825001
Q311.3675
95-th percentile19.9425
Maximum27.915
Range31.455
Interquartile range (IQR)6.865

Descriptive statistics

Standard deviation5.6951944
Coefficient of variation (CV)0.67369036
Kurtosis0.16384458
Mean8.4537269
Median Absolute Deviation (MAD)3.4350001
Skewness0.60173503
Sum201342.41
Variance32.435239
MonotonicityNot monotonic
2023-07-08T17:32:59.749007image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.599999905 31
 
0.1%
8.600000381 31
 
0.1%
10.39999962 29
 
0.1%
6.400000095 28
 
0.1%
7.900000095 28
 
0.1%
2 26
 
0.1%
1 25
 
0.1%
9.600000381 24
 
0.1%
8.100000381 24
 
0.1%
8.800000191 24
 
0.1%
Other values (18496) 23547
90.3%
(Missing) 2247
 
8.6%
ValueCountFrequency (%)
-3.539999974 1
< 0.1%
-3.534999967 1
< 0.1%
-3.529999971 1
< 0.1%
-3.5 2
< 0.1%
-3.485000014 1
< 0.1%
-3.455000043 1
< 0.1%
-3.452500045 1
< 0.1%
-3.442500055 1
< 0.1%
-3.425000072 1
< 0.1%
-3.397500086 1
< 0.1%
ValueCountFrequency (%)
27.91499987 1
< 0.1%
27.68749962 1
< 0.1%
27.56749983 1
< 0.1%
27.525 1
< 0.1%
27.405263 1
< 0.1%
27.37999992 1
< 0.1%
27.37500019 1
< 0.1%
27.35750008 1
< 0.1%
27.27631579 1
< 0.1%
27.26500015 1
< 0.1%

Front bearing temperature (°C)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20166
Distinct (%)84.7%
Missing2247
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean62.938399
Minimum9.1699998
Maximum81.295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:32:59.855258image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum9.1699998
5-th percentile34.895001
Q157.79
median68.967499
Q372.094998
95-th percentile74.055
Maximum81.295
Range72.125
Interquartile range (IQR)14.304998

Descriptive statistics

Standard deviation13.35603
Coefficient of variation (CV)0.21220798
Kurtosis2.7451663
Mean62.938399
Median Absolute Deviation (MAD)4.375
Skewness-1.68952
Sum1499003.9
Variance178.38355
MonotonicityNot monotonic
2023-07-08T17:32:59.954711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.5 11
 
< 0.1%
10.30000019 11
 
< 0.1%
18.70000076 9
 
< 0.1%
9.899999619 9
 
< 0.1%
10.19999981 9
 
< 0.1%
9.699999809 8
 
< 0.1%
10.39999962 7
 
< 0.1%
71.00499992 7
 
< 0.1%
72.47500038 7
 
< 0.1%
72.09499969 7
 
< 0.1%
Other values (20156) 23732
91.1%
(Missing) 2247
 
8.6%
ValueCountFrequency (%)
9.169999838 1
 
< 0.1%
9.217499876 1
 
< 0.1%
9.295000172 1
 
< 0.1%
9.300000191 5
< 0.1%
9.305000162 2
 
< 0.1%
9.315789624 1
 
< 0.1%
9.320000172 1
 
< 0.1%
9.330000114 1
 
< 0.1%
9.345000124 1
 
< 0.1%
9.350000143 1
 
< 0.1%
ValueCountFrequency (%)
81.29500008 1
< 0.1%
81.14999733 1
< 0.1%
80.99749947 1
< 0.1%
80.96750069 1
< 0.1%
80.81500168 1
< 0.1%
80.63499908 1
< 0.1%
80.51499901 1
< 0.1%
80.44999886 1
< 0.1%
80.25500031 1
< 0.1%
80.23999977 1
< 0.1%

Tower Acceleration X (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23817
Distinct (%)100.0%
Missing2247
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean50.179896
Minimum3.2420758
Maximum237.28179
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:33:00.058919image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum3.2420758
5-th percentile4.7280417
Q129.391882
median47.809321
Q368.999784
95-th percentile103.36813
Maximum237.28179
Range234.03972
Interquartile range (IQR)39.607902

Descriptive statistics

Standard deviation29.804504
Coefficient of variation (CV)0.59395308
Kurtosis0.22573138
Mean50.179896
Median Absolute Deviation (MAD)19.770132
Skewness0.50661698
Sum1195134.6
Variance888.30847
MonotonicityNot monotonic
2023-07-08T17:33:00.158343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.265513271 1
 
< 0.1%
88.1169363 1
 
< 0.1%
57.01803913 1
 
< 0.1%
67.82166948 1
 
< 0.1%
61.40462248 1
 
< 0.1%
55.28852449 1
 
< 0.1%
52.48540583 1
 
< 0.1%
71.30021321 1
 
< 0.1%
57.18512182 1
 
< 0.1%
72.59211712 1
 
< 0.1%
Other values (23807) 23807
91.3%
(Missing) 2247
 
8.6%
ValueCountFrequency (%)
3.242075849 1
< 0.1%
3.321028537 1
< 0.1%
3.342359513 1
< 0.1%
3.357094717 1
< 0.1%
3.380390453 1
< 0.1%
3.396232021 1
< 0.1%
3.417045975 1
< 0.1%
3.419179046 1
< 0.1%
3.422996187 1
< 0.1%
3.423810101 1
< 0.1%
ValueCountFrequency (%)
237.2817921 1
< 0.1%
234.5201759 1
< 0.1%
223.2469423 1
< 0.1%
214.1523712 1
< 0.1%
210.5179888 1
< 0.1%
203.8260487 1
< 0.1%
196.3120454 1
< 0.1%
195.5086425 1
< 0.1%
186.052269 1
< 0.1%
185.8519812 1
< 0.1%

Wind speed (m/s)
Real number (ℝ)

Distinct24547
Distinct (%)94.4%
Missing59
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean6.0503469
Minimum0.22526281
Maximum22.986319
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:33:00.256812image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.22526281
5-th percentile2.0706179
Q13.8952176
median5.5439574
Q37.7748543
95-th percentile11.746543
Maximum22.986319
Range22.761056
Interquartile range (IQR)3.8796367

Descriptive statistics

Standard deviation2.9590524
Coefficient of variation (CV)0.48907152
Kurtosis0.4139713
Mean6.0503469
Median Absolute Deviation (MAD)1.8684827
Skewness0.76788354
Sum157339.27
Variance8.7559908
MonotonicityNot monotonic
2023-07-08T17:33:00.357475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.920000076 11
 
< 0.1%
4.849999905 10
 
< 0.1%
3.799999952 10
 
< 0.1%
4.230000019 9
 
< 0.1%
4.119999886 9
 
< 0.1%
3.029999971 9
 
< 0.1%
3.690000057 9
 
< 0.1%
3.950000048 9
 
< 0.1%
3.529999971 9
 
< 0.1%
5.53000021 9
 
< 0.1%
Other values (24537) 25911
99.4%
(Missing) 59
 
0.2%
ValueCountFrequency (%)
0.2252628091 1
< 0.1%
0.2295191318 1
< 0.1%
0.2654440658 1
< 0.1%
0.2713621172 1
< 0.1%
0.2859752193 1
< 0.1%
0.2867813705 1
< 0.1%
0.2909250937 1
< 0.1%
0.3189375333 1
< 0.1%
0.3194814172 1
< 0.1%
0.3455813542 1
< 0.1%
ValueCountFrequency (%)
22.98631859 1
< 0.1%
22.42384105 1
< 0.1%
22.2278954 1
< 0.1%
20.57754068 1
< 0.1%
20.51229339 1
< 0.1%
20.48555956 1
< 0.1%
20.39130297 1
< 0.1%
20.3020545 1
< 0.1%
19.65130906 1
< 0.1%
19.58402009 1
< 0.1%

Tower Acceleration y (mm/ss)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23816
Distinct (%)> 99.9%
Missing2247
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean26.128814
Minimum3.2841205
Maximum269.1945
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:33:00.457314image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum3.2841205
5-th percentile4.8558072
Q114.887836
median22.57633
Q333.505504
95-th percentile59.122165
Maximum269.1945
Range265.91037
Interquartile range (IQR)18.617668

Descriptive statistics

Standard deviation17.036635
Coefficient of variation (CV)0.65202482
Kurtosis7.0291731
Mean26.128814
Median Absolute Deviation (MAD)8.9185897
Skewness1.7282004
Sum622309.96
Variance290.24694
MonotonicityNot monotonic
2023-07-08T17:33:00.560838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.824553287 2
 
< 0.1%
7.958044422 1
 
< 0.1%
29.705446 1
 
< 0.1%
20.55173843 1
 
< 0.1%
30.05092354 1
 
< 0.1%
26.47226057 1
 
< 0.1%
31.25222116 1
 
< 0.1%
19.48220838 1
 
< 0.1%
34.41643951 1
 
< 0.1%
32.99316709 1
 
< 0.1%
Other values (23806) 23806
91.3%
(Missing) 2247
 
8.6%
ValueCountFrequency (%)
3.284120494 1
< 0.1%
3.394452071 1
< 0.1%
3.44109953 1
< 0.1%
3.496588147 1
< 0.1%
3.530016017 1
< 0.1%
3.533664745 1
< 0.1%
3.555079913 1
< 0.1%
3.561114371 1
< 0.1%
3.603573881 1
< 0.1%
3.609277433 1
< 0.1%
ValueCountFrequency (%)
269.1944954 1
< 0.1%
251.3193106 1
< 0.1%
185.7556286 1
< 0.1%
158.93727 1
< 0.1%
157.6968445 1
< 0.1%
154.1202301 1
< 0.1%
145.960854 1
< 0.1%
144.9826616 1
< 0.1%
143.0860003 1
< 0.1%
142.9490614 1
< 0.1%

Metal particle count counter
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)0.1%
Missing2247
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean538.49906
Minimum532
Maximum545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size203.8 KiB
2023-07-08T17:33:00.645218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum532
5-th percentile533
Q1536
median539
Q3540
95-th percentile545
Maximum545
Range13
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.9522056
Coefficient of variation (CV)0.007339299
Kurtosis-0.92009858
Mean538.49906
Median Absolute Deviation (MAD)3
Skewness0.2369624
Sum12825432
Variance15.619929
MonotonicityIncreasing
2023-07-08T17:33:00.728411image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
540 5569
21.4%
536 4381
16.8%
545 3878
14.9%
539 2862
11.0%
533 2161
 
8.3%
534 1561
 
6.0%
535 892
 
3.4%
532 889
 
3.4%
538 786
 
3.0%
544 645
 
2.5%
Other values (4) 193
 
0.7%
(Missing) 2247
8.6%
ValueCountFrequency (%)
532 889
 
3.4%
533 2161
 
8.3%
534 1561
 
6.0%
535 892
 
3.4%
536 4381
16.8%
537 21
 
0.1%
538 786
 
3.0%
539 2862
11.0%
540 5569
21.4%
541 5
 
< 0.1%
ValueCountFrequency (%)
545 3878
14.9%
544 645
 
2.5%
543 29
 
0.1%
542 138
 
0.5%
541 5
 
< 0.1%
540 5569
21.4%
539 2862
11.0%
538 786
 
3.0%
537 21
 
0.1%
536 4381
16.8%

Interactions

2023-07-08T17:32:56.029007image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:41.623324image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.735557image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.042706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.231115image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.351357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.537893image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.744081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.088550image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.277693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.494217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.642650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.743176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.111702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:41.698300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.817933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.127335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.308421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.436450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.627227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.828495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.174370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.364785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.577121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.720389image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.823716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.206718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:41.785087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.913009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.219440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.396413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.534138image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.723459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.070347image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.268633image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.460282image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.668089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.807518image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.064471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.298679image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:41.875299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.004746image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.313660image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.486210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.629117image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.818822image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.165139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.363065image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.560449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.758579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.896625image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.151040image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.385937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:41.952531image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.225048image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.397602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.563911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.713322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.907949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.252813image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.446981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.647538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.841981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.974322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.231825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.479830image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.049536image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.314992image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.491962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.651216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.802283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.002136image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.345295image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.539842image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.741999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.932183image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.061758image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.320979image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.578593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.142559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.413908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.588451image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.743063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.899142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.100083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.444418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.638569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.839814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.028581image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.151767image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.416222image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.673978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.233032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.509478image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.684120image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.833940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.991728image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.195162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.537743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.732597image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.935923image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.120806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.240716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.507656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.766440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.318354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.600589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.778693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.922871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.084414image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.288907image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.632261image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.822930image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.030859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.210826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.325585image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.599256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.862426image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.407549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.697275image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.878289image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.013500image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.180157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.383811image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.727960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:50.917056image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.128335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.304648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.413976image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.690720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:56.950787image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.487110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.781769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:44.962832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.095184image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.266166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.472178image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.815145image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.006496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.218768image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.384716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.495535image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.774587image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:57.039574image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.565241image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.864530image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.049422image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.174584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.352690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.558936image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.902162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.092404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.306245image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.468899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.573341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.855715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:57.126146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:42.649708image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:43.951737image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:45.136752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:46.262122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:47.444751image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:48.648802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:49.995162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:51.182751image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:52.398110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:53.553823image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:54.656608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-08T17:32:55.940324image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-08T17:33:00.816829image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Power (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
Power (kW)1.0000.009-0.007-0.3030.7480.9900.989-0.0770.8930.6340.9510.820-0.196
Wind direction (°)0.0091.0000.893-0.0100.0240.0080.0030.1150.0120.0920.0440.0650.067
Nacelle position (°)-0.0070.8931.0000.0060.004-0.009-0.0130.117-0.0080.0780.0250.0490.063
blade_angle-0.303-0.0100.0061.000-0.579-0.313-0.3140.074-0.441-0.134-0.231-0.1220.004
Rear bearing temperature (°C)0.7480.0240.004-0.5791.0000.7490.7450.0760.8730.4470.6930.552-0.001
Rotor speed (RPM)0.9900.008-0.009-0.3130.7491.0000.998-0.0730.8950.6360.9450.819-0.194
Generator RPM (RPM)0.9890.003-0.013-0.3140.7450.9981.000-0.0920.8960.6350.9440.819-0.206
Nacelle ambient temperature (°C)-0.0770.1150.1170.0740.076-0.073-0.0921.000-0.063-0.081-0.104-0.1010.664
Front bearing temperature (°C)0.8930.012-0.008-0.4410.8730.8950.896-0.0631.0000.5330.8400.705-0.139
Tower Acceleration X (mm/ss)0.6340.0920.078-0.1340.4470.6360.635-0.0810.5331.0000.5640.867-0.108
Wind speed (m/s)0.9510.0440.025-0.2310.6930.9450.944-0.1040.8400.5641.0000.791-0.236
Tower Acceleration y (mm/ss)0.8200.0650.049-0.1220.5520.8190.819-0.1010.7050.8670.7911.000-0.169
Metal particle count counter-0.1960.0670.0630.004-0.001-0.194-0.2060.664-0.139-0.108-0.236-0.1691.000

Missing values

2023-07-08T17:32:57.257081image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-08T17:32:57.450093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-08T17:32:57.659051image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
02021-01-01 00:00:00-1.149693307.529525291.51269589.9899989.5625000.05.1934100.5300009.1700004.2655136.2736757.958044532.0
12021-01-01 00:10:00-6.286764304.697377291.51269589.9899989.7225000.01.3506440.1400009.2175004.1832216.25111910.159372532.0
22021-01-01 00:20:00-5.450236305.362149291.51269589.98999810.2150000.00.513259-0.5525009.2950004.8168355.74781210.320758532.0
32021-01-01 00:30:00-6.098972301.221778291.51269589.98999810.6075000.00.555549-0.9025009.4100005.4861226.1468129.587534532.0
42021-01-01 00:40:00-5.789542294.945783291.51269589.98999811.0450000.00.033127-0.8925009.5575005.5124775.3289759.551749532.0
52021-01-01 00:50:00-5.139206292.771682291.51269589.98999811.5475000.00.642587-0.7500009.7975006.5589296.4008759.964278532.0
62021-01-01 01:00:00-5.353969292.194240291.51269589.98999811.9055560.01.028318-0.65277810.0388895.4549335.3327299.577049532.0
72021-01-01 01:10:00-6.014679298.413538291.51269589.98999812.3325000.03.261169-0.53250010.3050005.2634105.44245010.047750532.0
82021-01-01 01:20:00-1.570091294.674845291.51269589.98999812.1425000.01.107474-0.73500010.4700005.5464664.7209889.925770532.0
92021-01-01 01:30:00-1.135822302.307789291.51269589.98999811.5475000.04.275809-0.59000010.3575005.7516935.22170612.716030532.0
# Date and timePower (kW)Wind direction (°)Nacelle position (°)blade_angleRear bearing temperature (°C)Rotor speed (RPM)Generator RPM (RPM)Nacelle ambient temperature (°C)Front bearing temperature (°C)Tower Acceleration X (mm/ss)Wind speed (m/s)Tower Acceleration y (mm/ss)Metal particle count counter
260542021-06-30 22:20:0040.63999927.92000018.219999NaNNaN8.14970.039978NaNNaNNaN3.47NaNNaN
260552021-06-30 22:30:0026.88999927.93000018.219999NaNNaN8.14969.880005NaNNaNNaN3.24NaNNaN
260562021-06-30 22:40:00-4.82000030.70000118.219999NaNNaN8.14969.979980NaNNaNNaN2.65NaNNaN
260572021-06-30 22:50:00-12.33000033.52000018.219999NaNNaN8.14970.010010NaNNaNNaN2.52NaNNaN
260582021-06-30 23:00:00-1.94000034.81000118.219999NaNNaN8.14970.159973NaNNaNNaN2.65NaNNaN
260592021-06-30 23:10:0062.04000145.54999934.750000NaNNaN8.14970.159973NaNNaNNaN3.71NaNNaN
260602021-06-30 23:20:00104.09999834.54000143.459999NaNNaN8.14970.080017NaNNaNNaN4.43NaNNaN
260612021-06-30 23:30:00107.62000334.57000043.459999NaNNaN8.14969.969971NaNNaNNaN4.59NaNNaN
260622021-06-30 23:40:0055.61000131.36000143.459999NaNNaN8.14969.840027NaNNaNNaN3.96NaNNaN
260632021-06-30 23:50:0019.11000133.41000043.459999NaNNaN8.14969.969971NaNNaNNaN3.31NaNNaN